Effect of mammographic screening from age 40 years on breast cancer mortality (UK Age trial):final results of a randomised, controlled trial

Copyright © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.BACKGROUND: The appropriate age range for breast cancer screening remains a matter of debate. We aimed to estimate the effect of mammographic screening at ages 40-48 years on breast cancer mortality. METHODS: We did a randomised, controlled trial involving 23 breast screening units across Great Britain. We randomly assigned women aged 39-41 years, using individual randomisation, stratified by general practice, in a 1:2 ratio, to yearly mammographic screening from the year of inclusion in the trial up to and including the calendar year that they reached age 48 years (intervention group), or to standard care of no screening until the invitation to their first National Health Service Breast Screening Programme (NHSBSP) screen at approximately age 50 years (control group). Women in the intervention group were recruited by postal invitation. Women in the control group were unaware of the study. The primary endpoint was mortality from breast cancers (with breast cancer coded as the underlying cause of death) diagnosed during the intervention period, before the participant's first NHSBSP screen. To study the timing of the mortality effect, we analysed the results in different follow-up periods. Women were included in the primary comparison regardless of compliance with randomisation status (intention-to-treat analysis). This Article reports on long-term follow-up analysis. The trial is registered with the ISRCTN registry, ISRCTN24647151. FINDINGS: 160 921 women were recruited between Oct 14, 1990, and Sept 24, 1997. 53 883 women (33·5%) were randomly assigned to the intervention group and 106 953 (66·5%) to the control group. Between randomisation and Feb 28, 2017, women were followed up for a median of 22·8 years (IQR 21·8-24·0). We observed a significant reduction in breast cancer mortality at 10 years of follow-up, with 83 breast cancer deaths in the intervention group versus 219 in the control group (relative rate [RR] 0·75 [95% CI 0·58-0·97]; p=0·029). No significant reduction was observed thereafter, with 126 deaths versus 255 deaths occurring after more than 10 years of follow-up (RR 0·98 [0·79-1·22]; p=0·86). INTERPRETATION: Yearly mammography before age 50 years, commencing at age 40 or 41 years, was associated with a relative reduction in breast cancer mortality, which was attenuated after 10 years, although the absolute reduction remained constant. Reducing the lower age limit for screening from 50 to 40 years could potentially reduce breast cancer mortality. FUNDING: National Institute for Health Research Health Technology Assessment programme.Peer reviewe

Modelling the overdiagnosis of breast cancer due to mammography screening in women aged 40 to 49 in the United Kingdom

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, andreproduction in any medium, provided the original work is properly cited

The Evaluation of Contralateral Breast Lesions in Breast Cancer Patients Using Reduction Mammoplasty

Purpose: This study evaluated the importance of routine pathological examination of contralateral breast specimens in breast cancer patients using reduction mammoplasty. Methods: The weight of breast tissue resected from the contralateral breast in 71 patients and the number of slices used for pathological evaluation were recorded. Breast lesions found in the contralateral breast and accompanying lesions with tumors were examined. Results: High risk proliferative lesions were reported in the contralateral breast of eight (11.2%) patients, and low-risk lesions were detected in 18 (25%). While the mean age of the patients with high-risk lesions was 45.6, it was 52.8 for the other patients (p = 0.036). Conclusion: Bilateral reduction mammoplasty may be beneficial to delineate some pathologies in contralateral breasts even in those patients with normal clinical and radiological findings. The incidental discovery of these pathologies is much more likely in young breast cancer patients

Breast cancer detection: radiologists’ performance using mammography with and without automated whole-breast ultrasound

ObjectiveRadiologist reader performance for breast cancer detection using mammography plus automated whole-breast ultrasound (AWBU) was compared with mammography alone.MethodsScreenings for non-palpable breast malignancies in women with radiographically dense breasts with contemporaneous mammograms and AWBU were reviewed by 12 radiologists blinded to the diagnoses; half the studies were abnormal. Readers first reviewed the 102 mammograms. The American College of Radiology (ACR) Breast Imaging Reporting and Data System (BIRADS) and Digital Mammographic Imaging Screening Trial (DMIST) likelihood ratings were recorded with location information for identified abnormalities. Readers then reviewed the mammograms and AWBU with knowledge of previous mammogram-only evaluation. We compared reader performance across screening techniques using absolute callback, areas under the curve (AUC), and figure of merit (FOM).ResultsTrue positivity of cancer detection increased 63%, with only a 4% decrease in true negativity. Reader-averaged AUC was higher for mammography plus AWBU compared with mammography alone by BIRADS (0.808 versus 0.701) and likelihood scores (0.810 versus 0.703). Similarly, FOM was higher for mammography plus AWBU compared with mammography alone by BIRADS (0.786 versus 0.613) and likelihood scores (0.791 versus 0.614).ConclusionAdding AWBU to mammography improved callback rates, accuracy of breast cancer detection, and confidence in callbacks for dense-breasted women

Machine Learning with Applications in Breast Cancer Diagnosis and Prognosis

Breast cancer (BC) is one of the most common cancers among women worldwide, representing the majority of new cancer cases and cancer-related deaths according to global statistics, making it a significant public health problem in today’s society. The early diagnosis of BC can improve the prognosis and chance of survival significantly, as it can promote timely clinical treatment to patients. Further accurate classification of benign tumours can prevent patients undergoing unnecessary treatments. Thus, the correct diagnosis of BC and classification of patients into malignant or benign groups is the subject of much research. Because of its unique advantages in critical features detection from complex BC datasets, machine learning (ML) is widely recognised as the methodology of choice in BC pattern classification and forecast modelling. In this paper, we aim to review ML techniques and their applications in BC diagnosis and prognosis. Firstly, we provide an overview of ML techniques including artificial neural networks (ANNs), support vector machines (SVMs), decision trees (DTs), and k-nearest neighbors (k-NNs). Then, we investigate their applications in BC. Our primary data is drawn from the Wisconsin breast cancer database (WBCD) which is the benchmark database for comparing the results through different algorithms. Finally, a healthcare system model of our recent work is also shown

Estimation of progression of multi-state chronic disease using the Markov model and prevalence pool concept

<p>Abstract</p> <p>Background</p> <p>We propose a simple new method for estimating progression of a chronic disease with multi-state properties by unifying the prevalence pool concept with the Markov process model.</p> <p>Methods</p> <p>Estimation of progression rates in the multi-state model is performed using the E-M algorithm. This approach is applied to data on Type 2 diabetes screening.</p> <p>Results</p> <p>Good convergence of estimations is demonstrated. In contrast to previous Markov models, the major advantage of our proposed method is that integrating the prevalence pool equation (that the numbers entering the prevalence pool is equal to the number leaving it) into the likelihood function not only simplifies the likelihood function but makes estimation of parameters stable.</p> <p>Conclusion</p> <p>This approach may be useful in quantifying the progression of a variety of chronic diseases.</p

Long-term prognosis of breast cancer detected by mammography screening or other methods

Introduction Previous studies on breast cancer have shown that patients whose tumors are detected by mammography screening have a more favorable survival. However, little is known about the long-term prognostic impact of screen-detection. The purpose of the current study was to compare breast cancer-specific long-term survival between patients whose tumors were detected in mammography screening and those detected by other methods. Methods Breast cancer patients diagnosed within five specified geographical areas in Finland in 1991-92 were identified (n=2,936). Detailed clinical, treatment and outcome data as well as tissue samples were collected. Women with in situ carcinoma, distant metastases at the primary diagnosis and women who were not operated were excluded. Main analyses were made with exclusions of patients with other malignancy or contralateral breast cancer followed by to sensitivity analyses with different exclusion criterias. Median follow-up time was 15.4 years. Univariate and multivariate analysis of breast cancer-specific survival were performed. Results Of patients included in the main analyses (n=1,884) 22% (n=408) were screen-detected and 78% (n=1,476) were detected by other methods. Breast cancer-specific 15-year survival was 86% for patients with screen-detected cancer and 66% for patients diagnosed by other methods (p<0.0001, HR=2.91). Similar differences in survival were also observed in women at screening age (50-69 years) as well as in clinically important subgroups, such as patients with small tumors ([less than or equal to]1cm in diameter) and without nodal involvement (N0). Women with breast cancer diagnosed by screening mammography had a more favorable prognosis compared to those diagnosed outside of screening program following adjustments according to patient age, tumor size, axillary lymph node status, histological grade and hormone receptor status. Significant differences in the risk of having future contralateral breast cancer according to method of detection was not observed . Conclusions Breast cancer detection in mammography screening is an independent prognostic factor in breast cancer and is associated with a more favorable survival also in long-term follow-up.BioMed Central open acces